Artificial Intelligence
Combining belief functions based on distance of evidence
Decision Support Systems
Fuzzy preference relations: Aggregation and weight determination
Computers and Industrial Engineering
Applying fuzzy linguistic preference relations to the improvement of consistency of fuzzy AHP
Information Sciences: an International Journal
Fuzzy hierarchical TOPSIS for supplier selection
Applied Soft Computing
A green supplier selection model for high-tech industry
Expert Systems with Applications: An International Journal
Expert Systems with Applications: An International Journal
Evaluation of knowledge management tools using AHP
Expert Systems with Applications: An International Journal
Modeling contaminant intrusion in water distribution networks: A new similarity-based DST method
Expert Systems with Applications: An International Journal
Supplier selection with an integrated methodology in unknown environment
Expert Systems with Applications: An International Journal
Supplier selection and performance evaluation in just-in-time production environments
Expert Systems with Applications: An International Journal
A new linguistic MCDM method based on multiple-criterion data fusion
Expert Systems with Applications: An International Journal
Strategic analysis of healthcare service quality using fuzzy AHP methodology
Expert Systems with Applications: An International Journal
Fuzzy AHP approach for supplier selection in a washing machine company
Expert Systems with Applications: An International Journal
A new fuzzy dempster MCDM method and its application in supplier selection
Expert Systems with Applications: An International Journal
Supplier selection using consistent fuzzy preference relations
Expert Systems with Applications: An International Journal
Assessment of E-Commerce security using AHP and evidential reasoning
Expert Systems with Applications: An International Journal
Simulation based fuzzy TOPSIS approach for group multi-criteria supplier selection problem
Engineering Applications of Artificial Intelligence
A fuzzy-Bayesian model for supplier selection
Expert Systems with Applications: An International Journal
Expert Systems with Applications: An International Journal
A Consensus Model for Group Decision Making With Incomplete Fuzzy Preference Relations
IEEE Transactions on Fuzzy Systems
Expert Systems with Applications: An International Journal
Risk analysis in a linguistic environment: A fuzzy evidential reasoning-based approach
Expert Systems with Applications: An International Journal
Knowledge-Based Systems
Short Communication: A new optimal consensus method with minimum cost in fuzzy group decision
Knowledge-Based Systems
Application of decision-making techniques in supplier selection: A systematic review of literature
Expert Systems with Applications: An International Journal
Environmental impact assessment based on D numbers
Expert Systems with Applications: An International Journal
The effects of a trust mechanism on a dynamic supply chain network
Expert Systems with Applications: An International Journal
A new decision-making method by incomplete preferences based on evidence distance
Knowledge-Based Systems
Hi-index | 12.05 |
Supplier selection is an important issue in supply chain management (SCM), and essentially is a multi-criteria decision-making problem. Supplier selection highly depends on experts' assessments. In the process of that, it inevitably involves various types of uncertainty such as imprecision, fuzziness and incompleteness due to the inability of human being's subjective judgment. However, the existing methods cannot adequately handle these types of uncertainties. In this paper, based on a new effective and feasible representation of uncertain information, called D numbers, a D-AHP method is proposed for the supplier selection problem, which extends the classical analytic hierarchy process (AHP) method. Within the proposed method, D numbers extended fuzzy preference relation has been involved to represent the decision matrix of pairwise comparisons given by experts. An illustrative example is presented to demonstrate the effectiveness of the proposed method.